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Twitter is one of the most popular social networks. Previous research found that users employ Twitter to communicate about software applications via short messages, commonly referred to as tweets, and that these tweets can be useful for requirements engineering and software evolution. However, due to their large number---in the range of thousands per day for popular applications---a manual analysis...
Rationale refers to the reasoning and justification behind human decisions, opinions, and beliefs. In software engineering, rationale management focuses on capturing design and requirements decisions and on organizing and reusing project knowledge. This paper takes a different view on rationale written by users in online reviews. We studied 32,414 reviews for 52 software applications in the Amazon...
As part of a research project that aims at proposing a new methodology for defining a series of rules for writing good requirements – often referred to as a Controlled Natural Language (CNL) – for the French Space Agency (CNES, Centre National d'Études Spatiales), we asked both experienced engineers and non-experts to fill in an online questionnaire in order to gather their perception about requirements...
Requirements Engineering (RE) has grown from its humble beginnings to embrace a wide variety of techniques, drawn from many disciplines, and the diversity of tasks currently performed under the label of RE has grown beyond that encom-passed by software development. We briefly review how RE has evolved and observe that RE is now a collection of best practices for pragmatic, outcome-focused critical...
In agile software development projects, software engineers prioritize implementation over documentation to eliminate needless documentation. Is the cost of missing documentation greater than the cost of producing unnecessary or unused documentation? Even without these documents, software engineers maintain other software artifacts, such as tickets in an issue tracking system (ITS) or source code committed...
The number of papers and articles on goals would suggest that goal-oriented requirements engineering is a well understood and mature area within the requirements engineering discipline. In particular, there is a wealth of published material on formal goal modelling approaches. However, the uptake of the goal approaches advocated by academics and researchers within real world settings appears to be...
Requirements Engineering plays a crucial role in coordinating the different stakeholders needed for safe aeronautics systems engineering. We conducted a qualitative study, using interviews and mockups, with fifteen industrial practitioners from four aeronautics companies, in order to investigate what tasks are actually performed by requirements engineers and how current tools support these tasks....
Choosing how to write natural language scenarios is challenging, because stakeholders may over-generalize their descriptions or overlook or be unaware of alternate scenarios. In security, for example, this can result in weak security constraints that are too general, or missing constraints. Another challenge is that analysts are unclear on where to stop generating new scenarios. In this paper, we...
Requirements Engineering (RE) is comprised of various tasks related to discovering, documenting, and maintaining different kinds of requirements. To accomplish these tasks, a Requirements Engineer or Business Analyst needs to retrieve and combine information from multiple sources such as use case models, interview scripts, and business rules. However, collecting and analyzing all the required data...
When Requirements Engineering(RE) models are unreasonably complex, they cannot support efficient decision making. SHORT is a tool to simplify that reasoning by exploiting the "key" decisions within RE models. These "keys" have the property that once values are assigned to them, it is very fast to reason over the remaining decisions. Using these "keys", reasoning about...
Software datasets play a crucial role in advancing automated software traceability research. They can be used by researchers in different ways to develop or validate new automated approaches. The diversity and quality of the datasets within a research community have a significant impact on the accuracy, generalizability, and reproducibility of the results and consequently on the usefulness and practicality...
Conflicts between non-functional requirements (NFRs) mean that achieving one requirement can impact another one. This can happen if a particular procedure (called "operationalizing softgoal" in the literature) favors the first characteristic but creates difficulty for the second one. Currently, the conflict identification uses catalogs to indicate conflicting NFRs. They focus on NFRs that...
Goal models help elicit, specify, analyze, and validate requirements as they capture hierarchical representations of system requirements, possible solutions, stakeholder objectives, and their relationships. In the early requirements phase, goal models aid requirements engineers in understanding the goals of stakeholders and exploring solution alternatives based on their impact on these goals. Despite...
Crowd RE is an emerging avenue for engaging the general public or the so called crowd in variety of requirements engineering tasks. Crowd RE scales RE by involving, potentially, millions of users. Although humans are at the center of Crowd RE, automated techniques are necessary (1) to derive useful insights from large amounts of raw data the crowd can produce; and (2) to drive the Crowd RE process,...
In this paper, we take up the second RE17 data challenge: the identification of requirements types using the "Quality attributes (NFR)" dataset provided. We studied how accurately we can automatically classify requirements as functional (FR) and non-functional (NFR) in the dataset with supervised machine learning. Furthermore, we assessed how accurately we can identify various types of NFRs,...
Since their introduction over a year ago, Google's TensorFlow package for learning with multilayer neural networks and their Word2Vec representation of words have both gained a high degree of notoriety. This paper considers the application of TensorFlow-guided learning and Word2Vec-based representations to the problems of classification in requirements documents. In this paper, we compare three categories...
This paper argues that for each advance in RE that has been made in the past 1000 years, the older practices were not replaced but still exist, and need to be studied empirically.
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